Author: kannumittal

The ever-changing arena of software development has given rise to numerous advanced programming languages that are encouraging smart programming with minimal bugs. Ever since the invention of the binary, programming languages have continued to evolve at a rapid pace, so much so that now we even have software that can interact with us just like another human being (Siri, Alexa)!

Over time, newer and better programming languages take over outdated programming languages, transforming the way we feed instructions to computers. As of 2018, these are going to be the hottest programming languages in software tech.

JavaScript

Over the years, JavaScript has continued to hold one of the top positions in programming languages across the world. And it looks like it’s not going to fade away anytime soon. The surge in the number of mobile users and consequent rise in the demand for web apps has increased the need for JavaScript and other JS-based frameworks such as React, Angular 5, and VUE.

Today, JavaScript has found its applications almost everywhere in the software sector, from front-end development to web app development. And it is the secret behind some of the most well-designed pages on the web. In a survey conducted by StackOverflow, it was found that nearly 85% of developers use JavaScript.

Swift

2014 saw the release of Swift by Apple. When Apple realized that coding in Objective C is quite frustrating, they saw an opportunity to bring in a new, and better programming language into the scene.

The language specification of Swift is comprehensive with many new features. With Swift, one can create high-quality, seamless, and stable applications. Also, Apple strongly relies on Swift while designing OS X and iOS apps and, given the simplicity of the language (easy to understand and work with), it can be safely concluded that Swift might just become one of the key programming languages in the upcoming 20 years.

Python

Python is a high-level programming language – an amalgamation of the best features of C and C++. What makes Python so amazing is the auto memory management coupled with its function and object-oriented functionality. It is highly dynamic and readable.

Python is used in web development, in designing GUIs (Graphic User Interfaces) such as video games, and a host of applications (audio/video, console, administration, etc.). Most of you are familiar with Instagram, YouTube, and Reddit. Wonder how they’re so smooth and well-crafted? Well, it’s Python guys!

Scala

If you’re into functional programming, Scala is the perfect programming language for you! Loaded with some fantastic features such as flexibility, scalability, real-time processing powers, and object-oriented nature, Scala has emerged to become a popular choice among software developers.

Since Scala was designed to run on JVM, so anything you code with Scala can run anywhere that is Java friendly! It is most widely used to develop web apps, Ad hoc scripting in REPL, and analyze data with Spark, to name a few.

R

Being a free open-source statistical programming language, R is currently the most favorite programming language of statisticians and data miners. Using the power of statistics, R can reveal patterns even in large datasets. The most commendable trait of R has to be its ability to solve complex problems.

R is in high demand among data scientists since it comes equipped with the fundamental functions necessary for data analysis along with some of the most useful statistical algorithms that are the requisites of data-driven science.

So, which among these are you planning to take up? Don’t think too much, pick a language, visit Coding Ninjas, get yourself enrolled in one of our courses, and see yourself sail through!

In this ever-augmenting world of technology, the smartphones have become a primary entity for the people to survive. As you know, Android is the most feasible and commonly used operating system for mobiles, and the need, scope, and value of the Android Developers are only increasing in the market.

If you have an interview around the corner, we recommend you go through this list of 12 essential interview questions. Also, even if you don’t have an interview, it’s still recommended to go through them – a little revision never hurts!

Describe the components of an Android Application Architecture.

Android Application Architecture has the following components:

Services: Services run in the background. For example, the facebook notifications, they continue to run, even if you switch the application.

Intent: It forms the interconnection between activities(actions performed on the screen) and the data passing mechanism by passing messages as per the request actions.

Resource Externalization: Externalization of resources is done for the ease to maintain, update and manage the resources.

Every Android application must possess an AndroidManifest.xml file in its root directory. This file presents essential information about your app to the Android system that it must have before it can run any of the app’s code.

What are the languages used for Android Application Development?

The android application development is written in Java(Android SDK) and C/C++(Android NDK).

What does ADT stand for?

ADT stands for Android Development Tool. It is used to develop and test the android applications.

What does ANR stand for?

ANR is a dialog box that appears when an application is not responding. It stands for “application not responding”.

What do you mean by ADB in Android?

Android Debug Bridge is a command line utility in Android SDK which lets the system communicate with a device. It can be used to control your device over USB from a computer, to copy files, install and uninstall apps, run shell commands, etc.

What are the key components of the Android Architecture?

Libraries

Linux Kernel

Android Framework

Android applications

What is an AdapterView in Android?

An AdapterView is a group of widgets in Android which includes the ListView, GridView, and Spinner. It also provides the layout of the underlying data for the view.

What do you mean by a Container in Android?

The container is a description of the views which holds the dynamic content. It is used to hold objects,widgets,labels,fields,icons,buttons.etc.

What are the notifications available in Android?

Toast Notification: It shows a pop-up message on the surface of the window.

Status Bar Notification: It shows the notification on the Status Bar.

Dialogue Notification: This type of notification is activity related.

What are the tools available in an Android SDK? Describe them.

Android: This tool allows you to manage the projects, AVDs and the components installed in the SDK.

ddms: It is used to debug Android applications.

Emulator: It is used to test the applications without using any physical device.

Draw 9-Patch: It is used to create a NinePatch graphic with the help of a WYSIWYG editor.

mksdcard: It is used to create a disk image that you can use with the emulator.

Sqlite3: This tool lets you access the SQLite files that are created and used by the Android applications

Proguard: This tool is used to shrink, optimize, and obfuscate your code by removing the unused code.

Traceview: It provides a graphical viewer to view the application logs in your application.

Adb: Adb stands for Android Debug Bridge. It is a versatile command line tool that helps you communicate with a device.

These questions skim through the basics of android app development, and the answers to these questions are a must know for anyone aiming for an android developer role. If you had any problems understanding any of these questions/answers, we recommend you drop by at Coding Ninjas. We have specially curated courses on Android App Development that’ll help you sail through the Android world with ease.

With the advent of smartphones, the number of mobile users across the world has been rising exponentially over the years. As we continue to become increasingly dependent on mobile applications for fulfilling many of our needs, the world of mobile apps is also steadily expanding. As of 2015, the number of mobile users globally was 4.43 billion, and by 2019, this figure is expected to hit 5.07 billion. Today, there are almost 1.6 million Android apps in Google Play Store and nearly 1.5 million iOS apps in the Apple App Store.

Such increasing numbers of mobile users and applications show that it’s a booming opportunity for app developers now! However, if you think that having a great idea for an app is the only thing you need to launch your first Android app, you are mistaken. There are a few things you need to know before leaping into the world of Android applications.

Let us now look at the MOST important things you need to know before building your first Android app.

Learning to Code

When you are keen to develop Android apps, you have to learn how to code. And to code, you need to have an in-depth knowledge of Java. It is a must. You have to start with the basics of app development and for this, you could either enroll yourself in online coding courses or browse through educational tutorials across YouTube, Google, and Bing. In case you want a more professional guidance to coding, try out the online coding courses by Coding Ninjas.

Another crucial thing you need to learn is XML. XML plays a big part in app design and development and learning it along with coding is a wise idea. And if you can, get your hands on this gem – Android Programming: The Big Nerd Ranch Guide.

Get Familiar With IDE

IDE or Integrated Development Environment provides you with the user interface where you can enter your code. Unlike softwares that require you to write two separate codes (one for compilation and one for running), IDEs let you compile and run the code simultaneously. They also allow programmers to test apps in an emulation environment that helps highlight errors and issues in the coding syntax, it also isolates and fixes bugs through debugging. The most popular IDE choice for Android is Android Studio (powered by Google) and Eclipse. However, while Android Studio is exclusively designed for Android app development, Eclipse is a much more generalized IDE.

Some amazing features of Android Studio are:

Gradle Integration

Advanced Code Completion

Fantastic User Interface

System Stability

Drag and Drop tool

Apart from IDE, app developers can also opt for Android SDK (Software Development Kit) that comprises of debugger, emulator, documentation, libraries, sample code, and tutorials. These tools will help you work on the glitches of your app and improve it.

Don’t Hesitate To Rely On Expert Help

Being a rookie, there will be times when you find yourself stuck on some problem or the other. There are many free online tools such as Stack Overflow, that’ll help you wiggle through such tricky situations in no time. And for everything else, there’s always Google!

Do Your Homework – Market Research

In-Depth market research is essential when you are developing an Android app. Market analyzations can provide you with valuable insights about your potential competitors, your target audience, and the kind of app that is demanded by your target audience. Knowing these key information pieces will allow you to understand the pain points of the mobile demographic and develop your app in a way that it can resolve those pain points seamlessly, enhancing the overall customer service experience. At Coding Ninjas, we take care of everything you need to know before, during, and after building an android application. Our expert instructors combined with an unmatched curriculum is what you should be looking for, if android app development is on your cards. Drop by at Coding Ninjas and have a look at a vast catalogue of courses and pick the one you like best!

Technology is rapidly transforming our world today. Smart and intelligent devices and machines have made our lives much more convenient and comfortable. And the driving factor behind this is Big Data. IBM maintains that 90% of the data that we have at our disposal today has been generated only in last two years! So one can only begin to imagine the extent of massive amounts of data being generated across the world every day, and it is bound to increase in the near future. And to process and analyze all this data into valuable information, we need Machine Learning and Artificial Intelligence.

Machine Learning (ML) is a tool of digital revolution aiming to transform the present computing processes into more efficient, accurate, and cost-effective ones. ML is a branch of computer science that automates analytical model building. The concept of ML is based on creating such systems that could learn from data and identify the data patterns to aid in the decision-making process. In 2015, Gartner published a report stating that over 75% of companies are investing in Big Data.

Smart machines can analyze vast chunks of data from multiple sources and identify the patterns within. When combined with IoT, ML can transform the face of healthcare. For instance, smart healthcare wearables incorporated with ML algorithms are now enabling doctors to monitor patients within the bounds of their homes. Remote monitoring has, in fact, become a boon for treating elderly patients for whom regular clinic visits can be very inconvenient. By regularly feeding personal data into the system, these smart wearables allow doctors to predict anomalies and take better decisions concerning the health of their patients.

Yes, the online retailers you so love for curating customized recommendations for you, all rely on ML. Machine Learning algorithms learn your preference patterns and display personalized suggestions based on your previous search activity. Furthermore, ML algorithms can be very resourceful in large organizations that often fall short of human staff. Smart machines that have been designed to decipher the meaning of specific interactions (content of emails, delivery notes, etc.) can automate generic replies and help ease the burden on the company staff. This will significantly enhance the customer service experience.

Finance

In the field of finance, ML holds tremendous potential. ML algorithms can be designed to monitor potential risks in business, volatility in trade metrics, and even help investors in managing their assets better. This is primarily because ML algorithms can detect potential threats and risks in the system in real-time, and help prevent such occurrences. Also, smart machines can help you to track your spending patterns and offer customized financial advice to you.

The most noticeable contribution of ML and AI has to be voice-interaction software. Apple’s Siri, Amazon Echo’s Alexa, Microsoft’s Cortana, and Google’s Assistant are redefining the entire user experience over devices. With these virtual voice assistants, you can literally control so many activities around you, whether you want to play music, or dim the lights of your room, or know the cricket scores, it’s all possible today, thanks to AI and Machine Learning. With advanced technological innovations, in the future, it may be possible for these virtual voice assistants to be able to understand the various nuances as well as the semantics of human languages.

With so many uses and applications of Machine Learning, it is also becoming one of the most sought-after fields. Today, most of the organization with the power of data are looking to use Machine learning and related techniques to provide their customers with a better experience.

So, if you’re someone who feels the adrenaline rush just by the thought of working on Machine Learning, we recommend you check out our course on the same. From supervised learning, unsupervised learning, to even Deep Learning – our course will help you gather the required knowledge to set your feet firmly in the world of Machine Learning.

As we see the world pacing towards an era where people are thriving to inculcate automaticity in everything possible, your choice of the way for blending with the advancing technology seems to be apt enough.

We won’t bore you with the well-known and overly discussed applications of this tech, like Tesla’s self-driving cars, featured recommendations on Amazon, or how machine learning is profoundly contributing in analytics, predictions, and calculations all over the world.

Rather, we’ll provide you with what you’re here for, making you dive right into the process of how machine learning actually works.

Question: How does ML work?

Answer: Algorithms!

Question: What programming language should I use to learn ML?

Answer: We have listed the languages as per the area of application and current analysis.

Python (used by 57% of the users):

Areas of application:

Sentiment Analysis(44%)

Natural Language Processing/ Chatbots(42%)

Web Mining(37%)

C/C++ (used by 43% of the users):

Areas of application:

AI in games(24%)

Robot Locomotion(27%)

Network Security and Cyber Attack Detection(26%)

Java (used by 41% of the users):

Areas of application:

Customer Support Management(26%)

Network Security and Cyber Attack Detection(23%)

Fraud Detection(22%)

R (used by 31% of the users):

Areas of application:

Sentiment Analysis(13%)

Bioengineering/ Bioinformatics(9%)

JavaScript (used by 28% of the users):

Areas of application:

Customer Support Management(10%)

Search Engines(9%)

As you can see, currently, Python is prioritized and highly recommended for use in ML. Python provides some ML libraries like, Tensorflow, Scikit Learn, Seaborn, Matplotlib, which could be used according to your Machine Learning projects.

Question: What are the types of Machine Learning?

Answer: There are primarily three types of Machine Learning:

Supervised Learning: Here, we make the machines learn by providing them with a training data set or labeled data, which includes the input data and the answers to it, called the response values. In supervised learning, by giving the machines these examples, we train them to make predictions for calculating the response to the new input values. So, we can say that supervised learning has model training values or the already labeled data used for predictions in future problems. Example: Using the previous house sales, we can predict the house sales in future.

Unsupervised Learning: Unlike supervised learning, in unsupervised learning, we do not have historical labels for prediction. In this case, we train the system to draw inferences from the input data without the labeled responses, look for patterns in the data and find a structure in it. For example, from the given information about heights and weights for the breeds of dogs, the computer can identify which breed does the dog belongs to.

Reinforcement Learning: We can say that this type of machine learning is inspired by behaviorist psychology, i.e., the computer learns decision making on its own using trial and error methods. Here, we train our computer by telling it, on its every move, that whether it made a right decision or not. This way, it gets to learn by its own behavior and implements this learning in the future decisions.

For problem-solving in ML, you’ll have to analyze the type of problem and try to figure out that which area of Machine Learning would be considered best for solving it. Once you know it, you can use the concerned algorithms for the solutions.

If you have decided to go further in this field, these are some of the algorithms you will get your hands on while solving the problems using ML:

Classification Algorithms

Anomaly Detection Algorithm

Regression Algorithm

Clustering Algorithm

Reinforcement Algorithm

For solving any problem using machine learning, you’ll have to carry out certain steps, that are, acquiring the data, cleaning the data, performing train test split, training the model using the training set, and at last, evaluating the model using the test set.

What we’ve talked about, is enough to give you a fair bit of insights into the world of Machine Learning. However, it goes without saying that AI and ML are the widest spreading fields of our time. It’s only fair to say that if you’re interested in this domain, you should look for courses that’ll help you get deeper insights.

Oh, did we say ML courses? We, at Coding Ninjas, have both offline as well as an online course for Machine Learning where we talk in depth about everything you need to know if you’re setting out to master Machine Learning. We recommend you give us a visit!

If you’re here, chances are, you’ve decided to enter the world of competitive programming. And now, like every other fresher, you’re confused about the language to pick, right?

Java vs. C/CPP has been an ongoing debate since the advent of the competitive program. None of these languages trump the others, and it’s all about your preferences and needs. However, if you’re an absolute beginner, these key points will help you make a more informed decision:

C/CPP:

C++ does not force object-oriented programming: Unlike Java, the C++ language doesn’t force object-oriented programming, it merely supports. It. CPP provides useful extensions that can facilitate object-oriented programming thus allowing you to enjoy the best of both worlds.

Parameterized types: The “template” keyword in C++ allows the coder to write generic implementations of algorithms which can come in quite handy in the long run. In C, one could write a generic list implementation with an element like:

A vast standard library: C++, being a successor of the mighty C, allows the full use of the standard C libraries as well as the advanced libraries of C++. The most useful library is the Standard Template Library (STL). The STL contains some valuable templates like searching and sorting routines and implementation of most-used algorithms. It also includes useful data structures like maps, sets, lists, trees, graphs, etc. All of the STL routines and data structures are tailored to specific programmer needs – all the programmer has to do is fill in the types.

For example, to implement Binary Search, Java requires us to write a custom function. Whereas, in C++ Binary Search STL routine is defined as

binary_search(startaddress, endaddress, valuetofind)

The above routine can be used without spending a lot of time on the logic behind something as trivial as binary search, thereby saving the coder’s time.

Java:

STL vs. containers: C++ provides well designed STLs, whereas Java has Containers. The benefit of containers over STLs is that there are a few situations where STL doesn’t have a direct solution. For example, in case of priority_queue in STL, it doesn’t support decrease-key operation which is required for implementations of essential algorithms like Prim’s and Dijkstra’s.

Exception Handling in Java is incomparable: Java is known and appreciated for being exceptional in exception handling. It trumps C/C++ in this aspect. For example, it’s a lot easier to trace an ArrayIndexOutOfBound segmentation fault in Java.

Time Limit Exceeds: This is where Java comes second to C++. If you’re using Java, you might come across a TLE error due to Java being slightly slower.

Big integer and Regular Expressions: One of the biggest advantages of Java over C++ is the availability of libraries like Biginteger, Regular Expressions, and geometry library. These libraries make day-to-day competitive programming challenges easier to tackle.

C++ vs Java

Java requires more lines of code: Writing codes in Java uses a lot of syntaxes. This makes Java a great tool by providing the developers with granular control over their code. But, competitive programming demands speed, so, it’s recommended to pick Java only if you have some prior knowledge of coding in Java.

STL vs. Containers: As we discussed above, STLs are tailor-made for competitive programmers, but some programmers still prefer containers.

C++ is more Popular: Be it the origin year or the comfort of use, but C++ outstands Java regarding the number of users that use the language.

C++ saves time: Java is no doubt slower than C regarding compilation and execution of the code. Couple that with the verbosity of Java codes and you’ll realize the amount of time you can save if you opt for CPP. During coding contests, you need to compile and run programs many times before you reach the desired output. Java takes a lot of time in this aspect, while C++ is a lot slower. Therefore, in limited time contests, C++ can help save time. However, many coding contests today provide different time limits for Java and C++ with that for Java being on a slightly higher end than C++. So, even if you choose Java as your sword, you won’t lose out on too much. Just be thorough in whichever language you choose.

Wrapping it up, C++ is till date the most preferred language followed by Java for competitive programming. However, ardent Java coders still use Java and beat other coders fair and square. C++ being more popular doesn’t make it the one for you. Eventually, it all boils down to your comfort and your needs. If you’ve been coding in C/C++, you shouldn’t switch to Java just because of its exception handling capabilities. Similarly, if you have a Java background and are competent at it, C++ shouldn’t be your choice only because of its benefits. Being confident in what language you chose is the key along with rigorous practice. We at Coding Ninjas make sure you don’t lack in either – come, join us, and see yourself excel!

An increasing number of people from all walks of life are waking up the importance of understanding coding and its underlying principles. From teachers, entrepreneurs, managers, inventors, to even students (not necessarily of Computer Science background), everyone is trying to get around the concepts of programming.

In today’s technology-oriented world, the knowledge of programming is an integral part of learning. Technological innovations surround us and make our lives much more convenient and reliable. If you understand the basics of coding and programming, you know how these innovations work. Not only that, but you’ll also be in a position to implement your ideas and who knows, maybe you’ll be the one creating the next big thing?

Like most advanced disciplines today, you can learn to code either by enrolling in a coding boot camp (offline) or an online coding course. Both of them have their distinct advantages and limitations. Let us get a deeper insight into them.

Classroom Coding Courses:

Better guidance

It is a known fact that a classroom or boot camp environment is a highly interactive one – since you are not only surrounded by counselors and mentors, but also by your classmates. If ever you are unable to grasp a concept or are confused about something, you always have others to guide you through your weak points. Face-to-face discussions are possible in such an environment which can be quite nurturing for your coding skills.

Focused curriculum

Classroom coding classes or coding boot camps usually have a stipulated period (12-15 weeks) during which they focus on teaching the basics of coding, and cover all the relevant topics that every fresher need, helping comprehensive knowledge about coding and programming. The syllabus is curated well-planned, making learning much more natural.

Collaborative learning

When you learn to code in a class with fellow students, you learn to interact and collaborate with them as a team aiming to accomplish a common aim. Coding often requires a team effort and stimulates real-life challenges that you’ll face in a work environment. It’s a great experience to have!

Networking

Coders are nothing short of a community. In a classroom coding environment, you get to meet a lot of people from varied backgrounds – and consequently build good connections with them. Making right contacts and expanding your network can open the door to new possibilities. Who knows, some of these people might even be a potential future colleague!

Online Coding Courses:

Flexibility

One of the most significant advantages of online coding courses is flexibility. You don’t need to commute for long hours to reach your class – your class starts right where you are! This makes it easier to learn to code as you can conveniently fit it into your schedule. You get to learn and interact with your mentor at your own pace and convenience. A survey conducted by The Learning House reported that almost 44% of students who took online courses showed remarkable improvements concerning their employment, for instance, obtaining a full-time job just within a year after graduation.

Affordable courses

When you enroll in an online course, you only need to pay an online application fee, the tuition fee, and maybe spend a little more on reference book supplies. It is much more affordable than classroom courses where you have to incur transportation costs, high tuition rates, and a few other additional costs.

Range of options

Online coding courses usually have a vast number of course topics under their umbrella. As you can study at your convenience, you get to choose from an array of exciting subjects – as time and location are not a limiting factor here.

Self-motivation

Online learning courses demand a lot of motivation and dedication on your part. You need to chalk out deadlines for various courses and topics, and you need to fit them into your busy schedule. Gradually, you not only develop time management skills but also become much more motivated and responsible.

We, at Coding Ninjas aim to provide you the best of both worlds through our flagship online courses. From C++, Java, Machine Learning, to even interview preparation, we try to bridge the gap between online and offline learning through our unique pedagogy. Our ultimate aim is to replicate the classroom experience in our online classes. For the same reason, we have created batch walls where students can easily discuss doubts, share notes, and form a network. The teaching assistants (TAs) are available online for 6-8 hours daily to clear any doubts you have, and to help you better, we maintain a strict 10:1 ratio of students to TAs.. Everything from the instructors, course material, assignments, etc., is the same as our offline classes. You just get to learn at your own pace and time, and also earn a certificate along the way. Can’t get better!

Our online classes also provide in-house code sharing functionalities like code pair where students can seamlessly share their coding screen with teaching assistants without using a third-party application. The students can avail the benefits of text and video chat to collaborate in real-time with their TAs and classmates. If you are someone who learns better through interaction, discussions, and brainstorming sessions, then our online courses are for you! Do drop by our course page to know more. To make sure you aren’t in any sorts of double minds, we also provide a free-trial of our online classes, so that you can get the feel of what it is all about!

What are you waiting for? We have early bird discounts, too. Come on in, quick!

There’s always one coder friend in any friend circle who’s an expert at writing efficient codes quickly. They can get their way across any programming problem because of their grassroots level understanding of things backed by extensive practice. If you, too, have one such friend, and you’re always in awe of them, let’s tell you their secret – competitive programming. More often than not, such sharp brains are a result of patience and perseverance developed through competitive programming. The ability to think on your toes even under pressure is a must have in any coder, and competitive programming helps you master that.

Like every other competitive parallel, competitive programming also aims at subjecting the participants to problem/s under strict time constraints Competitive programming helps you develop quick-thinking skills without feeling the pressure of time. This skill will take you a long way in any career of your choosing.

So, competitive programming tournaments are mind-sports that thoroughly test your logical reasoning skills primarily, and coding skills secondarily. These contests are held all over the year and are hosted by some of the respected organizations. Pioneer and the oldest among them is ACM – ICPC started in the 1970s.

Typically a competitive programming event is centered around a set of problems, presented to the participants (few hundred to a few thousands in number). Nature of the problem is often mathematical or logical. The primary objective of these online events is to have contestant write source code in a programming language (usually of their choosing) to test algorithm construction and implementation capabilities.

To excel at competitive programming, not only do you need to be fast, but also thorough with the basic concepts of programming and algorithms. Even the most challenging problem you’ll encounter can be broken down into simpler sub-problems that can be quickly solved if you’re aware of the underlying algorithms and data structures.

Like we said earlier, competitive programming is more of a stress-test than programming test. So, a few basic concepts other than the knowledge of coding and algorithms that’ll come handy are:

Common Sense

Complexity Analysis (Often underlooked by beginners, but, if you ignore it, you will understand its importance after a myriad number of TLEs)

Number Theory

Combinatorics & Probability

Geometry & Math in general

The art of debugging

Now, from a Computer Science perspective,

Binary Search

Sorting algorithms

String search algorithms

Dynamic Programming

Linked Lists

Trees

Disjoint sets

Depth First Search & Breadth First Search

Dijkstra’s algorithm

Such programming events can be broadly divided into two categories:

Short-term: duration being a few hours

Long-term: which may last from a few days to a few months. Some well-known examples are Google Code Jam, HackerRank, Facebook Hacker Cup, IOI, CodeChef, and many more.

Because competitive programming is all about applying right logics at the right time, people find it extremely cumbersome. But, there’s nothing that can’t be conquered with dedicated guidance. At Coding Ninjas, we realize the importance of such competitive programming contests for strengthening the logical capabilities of an individual. Not only that but winning at such cut-throat competitions also gives you the boost you need to grow stronger in your career.

Owing to their vastly varied problem sets, competitive programming events are a playground for coders as they give ample opportunity for honing the coding skills, while at the same time offering a chance of gauging their programming skills on a global scale. Apart from providing these opportunities, such events serve as an excellent platform for top scorers for attracting recruiters like Google, Facebook, IBM, and others. So this can be your launch pad in your journey of finding a career in hardcore programming with leading software/product-based companies.

Keeping all this in mind, we have come up with a dedicated and structured course that guides you through the intricacies involved with competitive programming. With the guidance from our expert instructors, students after training are ready to take on such challenges head-on and with confidence. We have both online and offline classes for you to try.

Just by the way – our online classes are just offline classes gone digital. All of the perks of the offline mode of learning combined with the comfort of studying at your time and pace. If you don’t believe us, do check it out for yourself. There are also trial classes available to make you doubly sure.

If you’re here, chances are you’ve just set your foot in the world of competitive programming. A few google searches here and there must’ve confused the hell out of you on what language to use, and now you’re in search of a comprehensive guide on the same. Don’t worry, we feel you!

But, before we proceed further, let’s clarify that language plays only a little role in competitive programming. So, we cannot claim that one language trumps the others. It’s all about your comfort and your understanding of various languages.

Having said that, if you’re still a beginner in the world of competitive coding, you need to know the things associated with the most preferred programming languages. Other than that, a grassroots level knowledge of core programming concepts like various data structures, sorting and searching algorithms, Prim’s, Dijkstra’s, and more graph and trees-related algorithms, will come in extremely handy during your competitions.

Competitive programming is all about solving in the fastest time and with the minimum complexity. More often than not, even the most complicated problem you’ll encounter can be broken down into smaller chunks, and knowledge of these basics will help you solve those chunks of problems quickly and collate them to form the final solution. Having essential algorithms at your fingertips will save you a lot of time and allow you to focus on more significant problems.

Now, with so much said and done, it’s time to look at the three most preferred programming languages for competitive coding.

C++:

C++ is the most preferred language for competitive programming mainly because of its STL. Short for Standard Template Library, the STL is a collection of C++ templates to help programmers quickly tackle basic data structures and functions such as lists, stacks, arrays, etc. It is a library of container classes, algorithms, and iterators.

STL is what ensure speed while coding in C++. Providing the basic data structures and functions as templates, STL cuts down a lot of your coding time. The power of C++ is undebatable because not only is it built on top of C (the mother of all programming languages) but also because it provides support for OOPS along with other features helpful during coding contests. Other than that, the verbosity of C++ codes is comparatively lesser than Java which makes it easier to code in.

Java:

Java is another classic programming language that’s extensively used for competitive programming. The fans of Java swear by the BigInteger class which is used for performing mathematical computations on large integers quickly. It comes in extremely handy during The exception handling is again something that Java is universally applauded for. It’s challenging to find segmentation faults in C++, but it’s easy to notice the ArrayIndexOutOfBound exception.

Although Java lacks STL, it has containers which perform pretty much the same function. Although the containers in Java are not as extensive as STL in C++, there are a few situations where STL doesn’t have a direct solution. For example, in case of priority_queue in STL, it doesn’t support decrease-key operation which is required for implementations of essential algorithms like Prim’s and Dijkstra’s. Java also has extensive support for geometrical problems. Its jawa.awt.geom package includes stuff like line-line/segment-segment intersection and polygon segment intersection. It comes in extremely helpful during some of the complicated problems of competitive programming that require you to deal with geometrical shapes and figures.

Python:

Over the years, Python has seen tremendous growth in the number of the people who use it. This can mainly be attributed to the fact that it takes very little time to come to grips with the (barely existent) syntax of Python – which is not the case with the other two languages we mentioned. One more reason that programmers are switching to Python is the REPL support. REPL, or Read-Eval-Print-Loop, lets you test your ideas under time constraints. Something that can come in quite handy during programming contests. Just like Java, Python too has a BigInteger class helpful for working with large integers.

However, if we talk about compilation speed, Python stands third in the list. Many times you might get a TLE (time limit exceeded) error for an algorithm in Python, but the same might get cleared if you code it in C++. To conclude, let’s reiterate that there’s no absolute best programming language. Each has a set of pros and cons and to be expert at competitive programming; you’ll need to have an extremely logical approach irrespective of the language you choose. At Coding Ninjas, we offer you an extensive course in Competitive Programming. Through that course, we aim to inculcate in you a sense of logical reasoning and problem-solving. From discussing the most important concepts involved in competitive programming to providing practice material, we’ve got it all.

The feeling of bagging a job is terrific, but the thought of being interviewed can make even the best of us sweat! With so many thoughts running through your mind, things can often go awry in an interview if you haven’t planned!

Usually, an interview is a highly stressed situation where you have got to perform well within the limited time and also make your thoughts crystal clear to the interviewer. Now, this calls for a whole new skill set altogether.

We know it can be challenging and so, let us guide you through this.

Generally, in coding and programming interviews, the emphasis lies on your logical reasoning skills along with the fundamental computer science concepts such as data structures, algorithms, design patterns. Basically, the skills that’ll come in handy during your job as a software engineer.

If you have interviews piled up in the near-future and despite being confident of your skills, you find yourself sweating merely at the thought of it, worry not – we’ve got you covered. Let’s help you not only tackle the interview but also ace it.

Pick your sword – choose a language

In almost all software companies, the interview process is the same, that is, they allow you to code in your preferred choice of programming language. The most common languages preferred for interviews are Python, Java, JavaScript, Ruby, C#, and C++. We recommend that you go with the language you are most familiar with.

Choosing dynamic languages such as Python, Ruby or JavaScript can be beneficial as these are permissive languages with compact syntax, flexible typing, along with the list and hash literals. However, these languages can become a liability when writing complex programs.

It’s a better idea to educate yourself about the products and services of the company you’re interviewing for. The more you know about their workings, the more you’ll know about the technologies they use. That ways, you’ll be able to guide yourself through the basics of their technological stack, the knowledge of which will surely make you stand out of the crowd.

Brush up on the frequently-asked interview questions and concepts

It is a known fact that a major part of the interview questions is based on algorithms and data structures. Knowing some of the basic interview concepts can be extremely helpful for a coding interview. So, having good knowledge about the following list of algorithms and data structures will come in handy for the interviews at most companies:

Searching and sorting algorithms

Concepts of arrays

Linked lists

Hash tables

Trees (notably, Binary Search Trees)

Breadth-first search, depth-first search

Dynamic programming

Complexity analysis

Practice makes you a better coder!

The more you practice, the better you get! Make it a point to practice algorithms and data structures in your preferred choice of programming language. Nowadays, running and testing codes has become very easy with the availability of online judges that allow you to practice questions online. Try to learn and understand the complexities of time and space in the operations of the programming language you choose to use. With such useful information at hand, you can minimize the mistakes and who knows, you might even earn bonus points from your interviewer!

So, keep on practicing!

Be logical, always.

Rome wasn’t built in a day. The journey from being a beginner to being a pro in coding takes time and it won’t work out till you’re willing to give it time. Computer programming languages are often difficult to grasp in the first go. After choosing your preferred programming language, select a particular area of this language. Now, try solving at least coding problems per day and keep on increasing the difficulty level as you progress. Set aside one day in the week to review the problems you’ve solved, see what errors you have made and try to learn how to avoid those mistakes again.

Coding is no less than an art. It requires a perfect sync of both heart and mind and is no less than writing poetry in that sense. There are two ways to go about preparing for an interview

Google “most asked questions”, cram them up, spit it out: You might or might not fail your interview, but you’ll definitely fail as an engineer if you choose this approach.

Be patient, take baby steps, enjoy your learnings, soak things slowly. The journey through the world of programming is beautiful and if you choose to rote learn instead of understand, you’ll be devoid of the beauty. Well, the rest is your choice.

Keep in mind at all times that when it comes to programming, cramming is never a solution. The interviewers always look for logical skills. Let’s, for instance, say that you were asked to derive the binary search algorithm. Now, if you’re from the lot who chose the first (easier) way out, you might or might not remember it – in any case, it won’t make a difference. The interviewer isn’t interested in you throwing the answer in his face. They’d rather have you come to the answer in front of their eyes. That ways, they’ll be able to gauge your problem solving skills too. And, if you impress them in this front, you’re pretty much in.

Therefore, at every step in your journey – right from you taking your first steps to you working as an expert software engineer, always choose the most logical route.

We at Coding Ninjas are here to make sure you live your dream of coding a product. Therefore, we like to help you all along the way. Whether it’s getting a hang of the programming languages to making you outshine your competition during interviews, we’ve got it all. Oh, and our flagship online programs are like nowhere else. You get the benefits of offline class combined with the comfort of studying at your time and pace. Don’t forget to drop by!